Regionalization of critical loads under uncertainty

The steady-state model PROFILE was used to perform Monte Carlo simulations of critical loads of acidity and exceedances of forest soils for 128 sites in the province of Scania, southern Sweden. Statistical tests showed that 100 sites had normal distributed critical loads and exceedances and that the variance of these parameters was statistically equal for all sites. Pooled estimates df the standard deviation was 0.19 and 0.31 kmol(c) ha(-1) yr(-1) for the critical loads and exceedances, respectively. Introduction of uncertainties, expressed as confidence intervals, in the cumulative distribution function for critical loads showed that overlaps between percentiles were substantial. The 5%-ile was systematically equal to the 57%-ile using a... (More)

The steady-state model PROFILE was used to perform Monte Carlo simulations of critical loads of acidity and exceedances of forest soils for 128 sites in the province of Scania, southern Sweden. Statistical tests showed that 100 sites had normal distributed critical loads and exceedances and that the variance of these parameters was statistically equal for all sites. Pooled estimates df the standard deviation was 0.19 and 0.31 kmol(c) ha(-1) yr(-1) for the critical loads and exceedances, respectively. Introduction of uncertainties, expressed as confidence intervals, in the cumulative distribution function for critical loads showed that overlaps between percentiles were substantial. The 5%-ile was systematically equal to the 57%-ile using a 67% confidence interval and equal to the 87%-ile when a 95% confidence level was chosen. The overlaps of percentiles cause a reduction of acidic deposition according to the mean value of the 5%-ile to protect only 68% of the ecosystem area with an 84% probability and not a guaranteed protection of 95% as if uncertainties did not exist. Thus, uncertainties make it possible to advocate reductions to levels of deposition below the 5%-ile of critical loads. (Less)

@article{8a2a601c-f9b6-423f-a9f1-50f69d2164af,
abstract = {The steady-state model PROFILE was used to perform Monte Carlo simulations of critical loads of acidity and exceedances of forest soils for 128 sites in the province of Scania, southern Sweden. Statistical tests showed that 100 sites had normal distributed critical loads and exceedances and that the variance of these parameters was statistically equal for all sites. Pooled estimates df the standard deviation was 0.19 and 0.31 kmol(c) ha(-1) yr(-1) for the critical loads and exceedances, respectively. Introduction of uncertainties, expressed as confidence intervals, in the cumulative distribution function for critical loads showed that overlaps between percentiles were substantial. The 5%-ile was systematically equal to the 57%-ile using a 67% confidence interval and equal to the 87%-ile when a 95% confidence level was chosen. The overlaps of percentiles cause a reduction of acidic deposition according to the mean value of the 5%-ile to protect only 68% of the ecosystem area with an 84% probability and not a guaranteed protection of 95% as if uncertainties did not exist. Thus, uncertainties make it possible to advocate reductions to levels of deposition below the 5%-ile of critical loads.},
author = {Barkman, A and Warfvinge, Per and Sverdrup, Harald},
issn = {1573-2932},
keyword = {regionalization,critical loads,forest,uncertainty,risk assessment},
language = {eng},
number = {4},
pages = {2515--2520},
publisher = {Springer},
series = {Water, Air and Soil Pollution},
title = {Regionalization of critical loads under uncertainty},
url = {http://dx.doi.org/10.1007/BF01186212},
volume = {85},
year = {1995},
}